3.2.6. Conclusions

From the available population projections, only those from the UN and IIASA fulfill the characteristics needed for use in long-term emission scenarios. First, the UN and IIASA data are published and available in the public domain, and second (more importantly) the scenarios consider uncertainty by developing more than just one, central demographic projection.

We use the medium UN projections in the SRES emissions scenarios because they have greater recognition internationally, and garner considerable attention as evident from the press focus devoted to the 1996 Revision (mentioned above). In addition, the UN assumption of replacement-level fertility in the long term, in contrast to the IIASA below-replacement assumption, is an important normative approach widely used heretofore in projections.

The rapid and slow demographic transition variants from IIASA projections remain attractive as the "high" and "low" population variants to be considered for the new IPCC emissions scenarios. The incorporation of a correlation between mortality rates and fertility (Lutz, 1996) is a logical first-order relationship not used in previous population variants and, in particular, not a feature of the UN variants. The two IIASA variants also represent well the uncertainty range as spanned by the probabilistic projections of Lutz et al. (1997), which represent an important methodological advance in the field. As shown in Figure 3-2, the resultant IIASA population range falls within the range of the UN projections.

Based on the above recommendations, Figure 3-8 compares the older IS92 population range with the population range described in this section. The population projections in IS92 scenarios comprise the UN 1992 medium-high and medium-low variants for the high and low ranges with the World Bank 1991 projection as the central case. As seen in Figure 3-8, the new range for SRES is somewhat narrower and lower than the IS92 range. The cause is partly the positive correlation between mortality rates and fertility rates within the IIASA variants, which mildly offset each other in terms of future population size. Another reason is the recent downward revision of the UN medium projection compared to earlier UN scenarios (as outlined above).

The literature suggests a general inverse correlation between economic growth rates and population growth rates. Higher economic growth rates in developing countries should correlate with lower population growth rates in long-term scenarios and vice versa, because of the importance of economic development in bringing about the demographic fertility transition. This represents a distinctive change from the IS92 trajectories. Importantly, there is still no quantitative basis for associating any particular economic growth curve with a particular population curve; this is a qualitative negative correlation only. Even more important is that income is not necessarily the best predictor of future fertility rates and many countries are currently moving through the demographic transition without a clear economic cause. Alternatively, some countries have failed to begin a fertility decline even though economic and social conditions have improved (e.g., Sathar and Casterline, 1998).

The inclusion of a household demographic unit, in addition to population, should be encouraged in future studies. The effect is linked to a strongly predicted demographic trend - aging. Also important are that smaller households are more energy intensive, per person, and that aging may continue to increase more rapidly than population in the future. These factors may increase CO₂ emissions (MacKellar et al., 1995), although senior citizens group-living is a tendency in some industrialized countries. Urbanization might also have a strong effect on emissions because of its effect on income distribution and thus energy consumption patterns around the world, although many of these effects are included implicitly in the models and parameters used in this report.

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